The question of what drives learners to adopt and use certain technologies over others, generally referred to as technology acceptance in the literature, is of interest to educational technology researchers, to policymakers, and developers in educational institutions. Technology acceptance models can inform adoption and implementation decisions. Despite the growing literature on technology ... [Show full abstract] acceptance, there is less evidence from countries with the lowest economic development indicators such as Nepal. The present study investigates the factors motivating technology use in the Nepali context. The study is grounded in an extended technology acceptance model (TAM) applied to using the internet for learning (not limited to online learning environments). The data were collected from 126 school students in Nepal (Mage = 15.19). We found empirical support for our proposed research model. There were strong relationships between computer self-efficacy and perceived enjoyment, and perceived enjoyment and behavioral intention. We found no influence of perceived usefulness or attitude on behavioral intention, contrary to theorized relationships and the empirical literature. Our findings show that the extended TAM translates to understudied populations such as Nepali secondary school students and suggests that it is sensitive to local situational differences that influence technology acceptance behaviors.